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During triage, process each fuzzing campaign separately as they may have
different base kernel revisions (e.g. if the newest revisions of the
kernel no longer build/boot under the specific kernel configuration).
Refactor the representation of the fuzzing targets in api.go.
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Track base crashes for (commit hash, config, arch) tuples.
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Keep the fuzz-step parameters in a separate structure to minimize the
field duplication.
It will also facilitate the reuse of the same syzkaller config in
several fuzzing configurations.
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Not always are fuzzing targets well represented by their own kernel
trees, so let's select a kernel tree and a fuzzing config separately.
Drop explicit priorities and instead just sort the lists of trees and
configs.
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We used to only upload them on triage failure, but let's improve the
inspectability even for successfully finished triage jobs.
Slightly refactor the controller API around the triage result
submission.
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The archive would be a useful source of debugging information.
Provide an HTTP endpoint that accepts a multipart form request with
the archived data.
Provide an *api.Client method to encapsulate the encoding of the data.
Add a test.
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Once a new kernel revision becomes available, build it to figure out
whether it's buildable. This information will be used in the triage step
to figure out the right base kernel revision.
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Provide an API to set up the reporting of finished sessions for which
syz-cluster collected reportable findings.
The actual sending of the results is to be done in a separate component
that would:
1) Call Next() to get the next report to send.
2) Call Confirm() to confirm that the report has been sent.
3) Call Upstream() if the report has been moderated and needs to be sent
to e.g. public mailing lists.
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In the previous version of the code, series-tracker was directly pushing
patch series into the DB and the controller auto-created fuzzing
sessions.
Mediate these via the controller API instead.
Instead of creating Session objects on the fly, pre-create them and
let processor take them one by one.
The approach has multiple
benefits:
1) The same API might be used for the patch series sources other than
LKML.
2) If the existence of Session objects is not a sign that we have
started working on it, it allows for a more precise status display
(not created/waiting/running/finished).
3) We could manually push older patch series and manually trigger
fuzzing sessions to experimentally measure the bug detection rates.
4) The controller tests could be organized only by relying on the API
offered by the component.
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Refactor the helper methods to reduce code duplication.
Add context argument support for GET methods.
Add a one minute deadline on top of the deadline imposed by the context.
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It lets immediately distinguish the series that were actually processed
from the series that were skipped early on.
By storing a string, we also make it apparent why exactly the series was
skipped.
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Findings are crashes and build/boot/test errors that happened during the
patch series processing.
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The basic code of a K8S-based cluster that:
* Aggregates new LKML patch series.
* Determines the kernel trees to apply them to.
* Builds the basic and the patched kernel.
* Displays the results on a web dashboard.
This is a very rudimentary version with a lot of TODOs that
provides a skeleton for further work.
The project makes use of Argo workflows and Spanner DB.
Bootstrap is used for the web interface.
Overall structure:
* syz-cluster/dashboard: a web dashboard listing patch series
and their test results.
* syz-cluster/series-tracker: polls Lore archives and submits
the new patch series to the DB.
* syz-cluster/controller: schedules workflows and provides API for them.
* syz-cluster/kernel-disk: a cron job that keeps a kernel checkout up to date.
* syz-cluster/workflow/*: workflow steps.
For the DB structure see syz-cluster/pkg/db/migrations/*.
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